These five get compared as if they were rivals. They aren't. Each one plugs a different leak, and you can run all five at once without any of them stepping on another.
I wrote one of them (jCodeMunch), so weigh my opinion accordingly. The descriptions and numbers for the other four are theirs, taken from their own projects.
What each one shrinks
| Tool | What it shrinks | Its own headline number | License |
|---|---|---|---|
| caveman | What the model writes back to you | ~75% fewer output tokens, averaged over 10 prompts | MIT |
| Ponytail | How much code the agent writes | 53% less code and 45% fewer tokens, over 39 tasks | MIT |
| RTK | What your terminal commands print | ~89% of the noise removed, across 30+ commands | MIT, with a paid cloud tier |
| Headroom | Everything flowing into the prompt | 47% to 92%, depending on the workload | Apache-2.0 |
| jCodeMunch | The code the agent reads | At least 95% fewer code-reading tokens (tiktoken, 15 task-runs, 3 repos) | Free for personal use, paid for commercial |
Those percentages are not comparable and they do not add up. Each one is a cut of a different pile. A 75% cut to your replies and a 95% cut to your file reads tell you nothing about your bill until you know how big each pile was.
caveman: the model talks less
caveman is a skill that tells the model to answer in telegraphic English. “New object ref each render. Use useMemo.” where it would have written you a paragraph. It has four levels of terseness and runs in Claude Code and 30-odd other agent hosts.
It works on the prose the model sends back, not on the code it writes. It also has a command that rewrites your CLAUDE.md in the same clipped style, which its author puts at about a 46% cut to that file on every session.
Reach for it when the agent's replies are long and you read them anyway. jCodeMunch vs caveman, in full
Ponytail: the agent writes less code
Ponytail is one prompt that makes the agent act like the senior developer who looks at your fifty lines and replaces them with one. It checks what the repo and the platform already have, then writes only what the task needs. Its own example: a date picker in 10 lines where the agent would have written 335.
Its author is clear that the goal was never the fewest tokens, and that validation, error handling, security and accessibility are not up for cutting. The savings are a side effect of writing less.
Reach for it when the agent keeps building more than you asked for. jCodeMunch vs Ponytail, in full
RTK: the terminal talks less
RTK is a single Rust binary that sits in front of the commands your agent runs and strips what comes back. Its own examples: a pytest run drops from 756 tokens to 24, and a git diff from about 21,500 to about 1,259.
It does nothing for code reading, and says so. It handles pytest, cargo test,
git status, docker logs and the rest of the things that print far more
than anyone needed.
Reach for it when your sessions are full of test and build output. jCodeMunch vs RTK, in full
Headroom: a compressor around the whole agent
Headroom wraps the agent (headroom wrap claude) and compresses what flows into the
prompt: tool results, logs, search hits, file contents. The compression is reversible, so the
model can ask for the original bytes back. It bundles RTK for shell output, which means you may
not need to install RTK separately.
Its reported savings range from 47% on codebase exploration to 92% on code search results and incident debugging. Of the three, it publishes the most about how it measures.
Reach for it when you want one layer across everything and you'd rather not pick. jCodeMunch vs Headroom, in full
jCodeMunch: the agent reads less code
Mine works a step earlier than the others. It indexes your repo once, and when the agent wants a function it gets that function, by name, where it would otherwise have opened the file. RTK and Headroom make what enters the prompt smaller. This one keeps most of it from being fetched at all.
It does nothing for terminal output or for what the model writes. Those jobs belong to RTK, caveman and Ponytail.
Reach for it when the agent keeps opening whole files to look at one part. What it does, for developers
Which one first?
Don't guess. Your agent keeps a log of every session on your own disk, and a short script will total it by tool. I wrote that up here: What's actually filling your Claude Code session?
Then read the top row.
Bashon top: RTK, or Headroom, which includes it.Readon top, with source files underneath: jCodeMunch.- An MCP server on top: look at that server before you install anything.
- The table looks fine and the long part is what the agent writes: caveman for the talk, Ponytail for the code.
If two rows are big, install two. That's the whole point of them being different tools.
Do they work together?
Yes. caveman and Ponytail work on what goes out, the other three on what comes in, and no two of them cover the same part. caveman even ships a piece of middleware that compresses the tool descriptions of MCP servers, mine included. Headroom has a flag meant for running beside a code-index server.
One caution that applies to all five, mine included: on a flat-rate plan none of this lowers your bill. It moves the point where you hit the limit.
Where to go from here
jCodeMunch vs caveman · jCodeMunch vs Ponytail · jCodeMunch vs RTK · jCodeMunch vs Headroom · All the comparisons, side by side